Independent innovation is the core of the national development strategy. After twenty years, Extenics made great progress in innovation theory, formal method and real application. Developing and manufacturing innovation software to help people develop intelligence, inspire creation is key for Extenics further developing. Now software model cannot meet the requirements of flexible alternate in innovation activities. To address this challenge, we propose to fusion agent, service and component for building autonomy, dynamic evolved, intelligent accumulated, great granularity intelligent service component (ISC), provide the good software entity for realization extension flexible thought. We try to expand extensible analysis, extension transformation, extension evaluation, dependent function and so on to services, according to extension innovation method dynamic integrate them into extension intelligent service system (EISS), finally establish a wise extension innovation software model. For software modeling provides a new way.

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Modeling Extenics Innovation Software by Intelligent Service Components

A data classification system comprising a server adapted to receive data elements from a computer network, compute a distance between the elements and a plurality of representative elements such that where the distance is less than a threshold, the input elements are associated with the representative element and where the distance is not less than the threshold, the input element is stored as a new representative element. A method of classifying network traffic is further disclosed that can include providing a server adapted to receive data from a network, compute a distance between the data elements and representative data elements such that where the distance is less than a threshold, the input elements are associated with the representative element and where the distance is not less than the threshold, the input element is stored as a new representative element.

System, method and apparatus for classifying digital data

Method for searching revolved body component process

The invention provides a process-adjustment choosing analysis method based on a multidimensional correlation function. The process-adjustment choosing analysis method comprises the steps of firstly, determining a plurality of influences caused by process adjustment on an extended manufacturing chain, secondly, establishing a calculation process for calculating influence values from an influence relationship matrix and retrieval based on examples, respectively, and thirdly, introducing a quantitative calculation method of the multidimensional correlation function for obtaining a process solution expected by a master enterprise from a process adjustment scheme set, inputting the calculated values of the influences on process adjustment into the multidimensional correlation function and finally obtaining the process adjustment scheme most perfectly according with the constraint demand of the master enterprise by virtue of point position determination and dimension reduction calculation. The process-adjustment choosing analysis method based on the multidimensional correlation function is combined with the relationship matrix ad based on example search and has excellent reliability.

Process-adjustment choosing analysis method based on multidimensional correlation function

The present invention provides a customized product similarity calculation method based on a structure editing operation, which relates to a product design configuration process in mass customization production. The method comprises: first, performing an analysis on a structure editing operation, and defining weights of different editing operations when considering different types of parts; second, constructing a correlative relationship between a local difference and a whole similarity, defining the local difference and whole similarity of the editing operation by using an expert grade, and training and calculating a weight matrix and a threshold matrix based on a correlative relationship of a neural network; and third, calculating a product similarity. The present invention provides a customized product similarity calculation method based on a structure editing operation, in which the correlative relationship between the local difference and the whole similarity of a product is considered and different types of product components are combined.

Customized product similarity calculation method based on structure editing operation

The invention relates to a parts classification method based on expansible cluster, which comprises the following steps: 1) the node domain of the structural characteristic of parts is extracted; 2) the characteristic variable numerical value v and the interval V of the parts are determined; 3) the distance formula of each part structure is established; 4) the structural relevancy T(i, j) of parts Ri and Rj is determined; 5) numerical analysis is carried out to a symmetric matrix M; 6) the average relevancy numerical value of cluster analysis is established; 7) the n minus 2 symmetric matrix is obtained by utilizing the algorithm process of step 5) to the newly formed n minus 1 symmetric matrix, the processes are circulated, and when the minimum relevancy is more than K value, the cluster process is terminated and a unique cluster result is obtained: the category of products and the parts of each category. The invention provides a part classification method based on the expansible cluster, which has clear relevancy analysis, high classification efficiency and high accuracy.

Part classification method based on developable clustering

Case-based reasoning (CBR) is an effective method that integrates reasoning methodology and represents related knowledge in a domain. The success of a CBR system largely depends on case retrieval, and the similarity and determination of weight for each case features have a significant influence on the efficiency and accuracy of case retrieval. The aim of the research is to improve the efficiency and accuracy of case retrieval. Analyzing the deficiency of similarity measures based on the classical distance, different similarity measures are proposed for different kinds of attribute values based on the extension distance, especially the similarity model between numerical and set considered the customer’s preference. The standard deviation related with the similarity is introduced to distribute the dynamic attribute’s weights which also considered the customer’s interest, but not the traditional methods that the weight is a constant if determined. The presented methods will enable the system to retrieve the more similar case correctly so that reducing case adaptation. In this study, an electric drill is used as a case to verify the usefulness and effectiveness of the similarity measurements and weight assignments. It is demonstrated that this method is more beneficial to case retrieval compared with other methods.Copyright © 2008 by ASME

A Similarity Measure Based on Extension Distance and Its Application in CBR

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Part classification method based on developable clustering

A Similarity Measure Based on Extension Distance and Its Application in CBR